Ultrasensitive and Ultraprecise Pressure Sensors for Soft Systems

ZnO Nanostructure-Based Flexible Pressure Sensors Deposited on Filter Paper for Wearable Application

Flexible pressure sensors have broad prospects in smart wearables, healthcare, and human-computer interaction. Nevertheless, flexible pressure sensors still face numerous thorny challenges. It has become a crucial problem to skillfully design and successfully achieve flexible pressure sensors with both a high sensing range and ultrahigh sensitivity. The sensor is designed and realized with inspiration drawn from the layered microstructure of human skin, and hierarchical structure flexible pressure sensors are fabricated, where PDMS microstructures/MWCNTs act as the top electrode, filter paper/ZnO nanostructures/MWCNTs act as the intermediate active layer, and an Ag interdigitated electrode acts as the bottom electrode. The sensing performance of the sensor is investigated to develop the application of pressure sensors for human health detection in daily life, and a pressure sensor array is prepared to investigate the detection of spatial pressure distribution. Sensors based on paper and PDMS can achieve low-pressure detection (30 Pa), high sensitivity (261.38 kPa-1), fast response time (∼73.8 ms), and excellent cyclic stability (10 000 cycles). Finally, the sensor demonstrates its functionality by lighting up a small lamp, which confirms that the as-prepared pressure sensor has excellent application scenarios and is beneficial for the development of flexible electronic devices.

Superlow-Noise Quasi-2D Vertical Tunneling Tactile Sensor for Fine Liquid Dynamic Recognition

To achieve high-precision intelligent tactile recognition and hyperfine operation tasks, tactile sensors need to possess the ability to discriminate minute pressures within the range of human perception. However, due to the lack of methodologies for noise suppression, existing tactile sensing mechanisms are inferior in pressure resolution. In this work, we emulate the structure of biological fingertip Merkel cells to develop a quasi-2D vertical tunneling tactile sensor based on conformal graphene nanowalls-hexagonal boron nitride-graphene (CGNWs-hBN-Gr) van der Waals (vdWs) heterojunctions. Tunneling channel modulation of this heterojunction simulates the ion gating mechanism of piezo (PZ) proteins and greatly reduces the noise power spectral density (PSD) to 2.22 × 10-24 A2/Hz at 10 Hz, which is 3 orders of magnitude lower than that of the sensor without an hBN layer. The noise equivalent pressure (NEPr) was as low as 7.96 × 10-3 Pa. Multiscale conformal micro- and nanostructured CGNWs further promote an ultrahigh sensitivity of 1.99 × 106 kPa-1, and the sensor demonstrates a high signal-to-noise ratio (SNR) of 68.76 dB and a resolution of 1/10,000. The minimum identifiable loading of 2 Pa at a pressure of 20 kPa is less than the sensing threshold value of human skin. An ultraresolution sensor could be used to evaluate different liquid properties by detecting complex hydrodynamic changes during artificial touching of liquids via a fingertip. Combined with the TacAtNet model, this sensor distinguishes between different liquids with a resolution accuracy of 98.1% across five distinct alcohol concentrations.

Revisiting the "Stick-Slip" Process via Magnetism-Coupled Flexible Sensors with Bioinspired Ridge Architecture

"Stick-slip" phenomenon that occurs when human fingertip scans across a specific surface is essential to perceive the interactions between skin and the surface. Understanding the "stick-slip" behavior is important for bionic flexible system in applications from advanced robotics to intelligent tactile sensors. However, it is often overlooked owing to the limitations to mimic the soft skin that can tangentially deform/recover with informative electrical feedback. Here, a sandwich-type device with deformable ridge-layer is proposed to analyze the characteristic of stick/slip states in "stick-slip" process. Specifically, it is observed that fast recovery of the sensing architecture is caused by dynamic slip phase that generates periodical signals based on principle of induction. The results experimentally show that periods of the electrical pulses are dependent on factors such as inherent properties (e.g., modulus and geometry) and operational parameters (e.g., scanning speed and normal load), which is consistent with the theoretical model. Furthermore, it is found that the transition between "stick-slip" and full slip could qualitatively reflect interfacial properties such as moisture, roughness, and topology. It is expected that the results can strengthen the understanding of "stick-slip" behavior when fingertip interacts with a surface and provide guidance of flexible sensor design to enrich the biomimetic perceptions.

Boosting Sensitivity of Cellulose Pressure Sensor via Hierarchically Porous Structure

Pressure sensors are essential for a wide range of applications, including health monitoring, industrial diagnostics, etc. However, achieving both high sensitivity and mechanical ability to withstand high pressure in a single material remains a significant challenge. This study introduces a high-performance cellulose hydrogel inspired by the biomimetic layered porous structure of human skin. The hydrogel features a novel design composed of a soft layer with large macropores and a hard layer with small micropores, each of which contribute uniquely to its pressure-sensing capabilities. The macropores in the soft part facilitate significant deformation and charge accumulation, providing exceptional sensitivity to low pressures. In contrast, the microporous structure in the hard part enhances pressure range, ensuring support under high pressures and preventing structural failure. The performance of hydrogel is further optimized through ion introduction, which improves its conductivity, and as well the sensitivity. The sensor demonstrated a high sensitivity of 1622 kPa-1, a detection range up to 160 kPa, excellent conductivity of 4.01 S m-1, rapid response time of 33 ms, and a low detection limit of 1.6 Pa, outperforming most existing cellulose-based sensors. This innovative hierarchically porous architecture not only enhances the pressure-sensing performance but also offers a simple and effective approach for utilizing natural polymers in sensing technologies. The cellulose hydrogel demonstrates significant potential in both health monitoring and industrial applications, providing a sensitive, durable, and versatile solution for pressure sensing.

Crimean-Congo hemorrhagic fever: Pathogenesis, transmission and public health challenges

The dangerous Crimean-Congo hemorrhagic fever virus (CCHFV), an encapsulated negative-sense RNA virus of the family Nairoviridae, is transmitted from person to person via ticks. With a case fatality rate between 10% to 40%, the most common ways that the disease may spread to humans are via tick bites or coming into touch with infected animals' blood or tissues. Furthermore, the transfer of bodily fluids between individuals is another potential route of infection. There is a wide range of symptoms experienced by patients throughout each stage, from myalgia and fever to extreme bruising and excess bleeding. Tick management measures include minimising the spread of ticks from one species to another and from people to animals via the use of protective clothing, repellents, and proper animal handling. In order to prevent the spread of illness, healthcare workers must adhere to stringent protocols. Despite the lack of an authorised vaccine, the main components of treatment now consist of preventative measures and supportive care, which may include the antiviral medicine ribavirin. We still don't know very much about the virus's mechanisms, even though advances in molecular virology and animal models have improved our understanding of the pathogenesis of CCHFV. A critical need for vaccination that is both safe and effective, as well as for quick diagnosis and efficient treatments to lessen the disease's impact in areas where it is most prevalent. Important steps towards lowering Crimean-Congo hemorrhagic fever mortality and morbidity rates were to anticipatethe future availability of immunoglobulin products.

Constructing High-Performance Composite Epoxy Resins: Interfacial π-π Stacking Interactions-Driven Physical Rolling Behavior of Silica Microspheres

The intrinsic compromise between strength and toughness in composite epoxy resins significantly constrains their practical applications. In this study, a novel strategy is introduced, leveraging interfacial π-π stacking interactions to induce the "rolling behavior" of microsphere fillers, thereby facilitating efficient energy dissipation. This approach is corroborated through theoretical simulations and experimental validation. The resulting composite epoxy resin demonstrates an impressive 49.8% enhancement in strength and a remarkable 358.9% improvement in toughness compared to conventional epoxy resins, accompanied by substantially reduced hysteresis. Moreover, this system achieves reversible closed-loop recyclability and rapid repair capabilities. The preliminary demonstration of "force-temperature equivalence" further establishes a novel pathway for the design of high-performance composite epoxy materials.

Multi-Level High Entropy-Dissipative Structure Enables Efficient Self-Decoupling of Triple Signals

The theory of high entropy-dissipative structure is confined to high-entropy alloys and their oxide materials under harsh conditions, but it is very difficult to obtain high entropy-dissipative structure for smart sensors based on polymers and metal oxides under mild conditions. Moreover, multiple signal coupling effect heavily hinder the sensor applications, and current multimodal integrated devices can solve two signal-decoupling, but need very complicated process way. In this work, new synthesis concept is the first time to fabricate high entropy-dissipative conductive layer of smart sensors with triple-signal response and self-decoupling ability within poly-pyrrole/zinc oxide (PPy/ZnO) system. The sensor (SPZ20) amplifies pressure (17.54%/kPa) and gas (0.37%/ppm), reduces humidity (0.41%/% RH) and temperature (0.12%/°C) signals, simultaneously achieving the triple self-decoupling effect of pressure and gas in the complex temperature-humidity field because of the enlarged pressure-contact area, enhanced gas-responsive sites, altered vapor path and its own heat insulation function. Additionally, it inherits the strong robustness (500 rubbing, washing, and heating or freezing cycles) and endurance (10 000 photo-purification cycles) of traditional high-entropy materials for information transmission and smart alarms in emergencies or harsh environments. This work gives a new insight into the multiple-signal response and smart flexible electronic design from natural fibers.

Flexible Piezoresistive Film Pressure Sensor Based on Double-Sided Microstructure Sensing Layer

Flexible thin-film pressure sensors have garnered significant attention due to their applications in industrial inspection and human-computer interactions. However, due to their ultra-thin structure, these sensors often exhibit lower performance, including a narrow pressure response range and low sensitivity, which constrains their further application. The most commonly used microstructure fabrication methods are challenging to apply to ultra-thin functional layers and may compromise the structural stability of the sensors. In this study, we present a novel design of a film pressure sensor with a double-sided microstructure sensing layer by adopting the template method. By incorporating the double-sided microstructures, the proposed thin-film pressure sensor can simultaneously achieve a high sensitivity value of 5.5 kPa-1 and a wide range of 140 kPa, while maintaining a short response time of 120 ms and a low detection limit. This flexible film pressure sensor demonstrates considerable potential for distributed pressure sensing and industrial pressure monitoring applications.

Intelligent Song Recognition via a Hollow-Microstructure-Based, Ultrasensitive Artificial Eardrum

Artificial ears with intelligence, which can sensitively detect sound-a variant of pressure-and generate consciousness and logical decision-making abilities, hold great promise to transform life. However, despite the emerging flexible sensors for sound detection, most success is limited to very simple phonemes, such as a couple of letters or words, probably due to the lack of device sensitivity and capability. Herein, the construction of ultrasensitive artificial eardrums enabling intelligent song recognition is reported. This strategy employs novel geometric engineering of sensing units in the soft microstructure array (to significantly reduce effective modulus) along with complex song recognition exploration leveraging machine learning algorithms. Unprecedented pressure sensitivity (6.9 × 103 kPa-1) is demonstrated in a sensor with a hollow pyramid architecture with porous slants. The integrated device exhibits unparalleled (exceeding by 1-2 orders of magnitude compared with reported benchmark samples) sound detection sensitivity, and can accurately identify 100% (for training set) and 97.7% (for test set) of a database of the segments from 77 songs varying in language, style, and singer. Overall, the results highlight the outstanding performance of the hollow-microstructure-based sensor, indicating its potential applications in human-machine interaction and wearable acoustical technologies.

Stretchable Piezoresistive Pressure Sensor Array with Sophisticated Sensitivity, Strain-Insensitivity, and Reproducibility

This study delves into the development of a novel 10 by 10 sensor array featuring 100 pressure sensor pixels, achieving remarkable sensitivity up to 888.79 kPa-1, through the innovative design of sensor structure. The critical challenge of strain sensitivity inherent is addressed in stretchable piezoresistive pressure sensors, a domain that has seen significant interest due to their potential for practical applications. This approach involves synthesizing and electrospinning polybutadiene-urethane (PBU), a reversible cross-linking polymer, subsequently coated with MXene nanosheets to create a conductive fabric. This fabrication technique strategically enhances sensor sensitivity by minimizing initial current values and incorporating semi-cylindrical electrodes with Ag nanowires (AgNWs) selectively coated for optimal conductivity. The application of a pre-strain method to electrode construction ensures strain immunity, preserving the sensor's electrical properties under expansion. The sensor array demonstrated remarkable sensitivity by consistently detecting even subtle airflow from an air gun in a wind sensing test, while a novel deep learning methodology significantly enhanced the long-term sensing accuracy of polymer-based stretchable mechanical sensors, marking a major advancement in sensor technology. This research presents a significant step forward in enhancing the reliability and performance of stretchable piezoresistive pressure sensors, offering a comprehensive solution to their current limitations.

Achieving Ultrahigh DC-Power Triboelectric Nanogenerators by Lightning Rod-Inspired Field Emission Modeling

Direct current triboelectric nanogenerators (DC-TENGs) are a groundbreaking technology to capture micromechanical energy from the natural environment, which is crucial for directly powering sensor networks. However, the research bottleneck in enhancing the triboelectric electrification capability and charge storage capability of dielectrics has hindered the overall performance breakthroughs of the DC-TENG. Here, a field emission model-based DC-TENG (FEM-TENG) is proposed, inspired by lightning rods. The enhanced local electric field between dielectric materials and electrodes induces strong electron tunneling, which improves charge neutralization on the surface of materials and their internal charge storage space, thereby utilizing the dielectric volume effect effectively and strengthening triboelectricity. Guided by the field emission model, the FEM-TENG with a historic crest factor of 1.00375 achieves a groundbreaking record of an average power density of 16.061 W m-2 Hz-1 (1,591 W m-3 Hz-1), which is 5.36-fold of the latest DC-TENG. In particular, the FEM-TENG with high durability (100%) truly realizes the collection of breeze energy and continuously drives 50 thermohygrometers. Four additional applications exemplify the FEM-TENG, enabling comprehensive sensing of land, water, and air. This work proposes a paradigm strategy for the in-depth utilization of dielectric films, aiming to enhance the output power of DC-TENGs.

Biomimetic Multimodal Receptors for Comprehensive Artificial Human Somatosensory System

Electronic skin (e-skin) capable of acquiring environmental and physiological information has attracted interest for healthcare, robotics, and human-machine interaction. However, traditional 2D e-skin only allows for in-plane force sensing, which limits access to comprehensive stimulus feedback due to the lack of out-of-plane signal detection caused by its 3D structure. Here, a dimension-switchable bioinspired receptor is reported to achieve multimodal perception by exploiting film kirigami. It offers the detection of in-plane (pressure and bending) and out-of-plane (force and airflow) signals by dynamically inducing the opening and reclosing of sensing unit. The receptor's hygroscopic and thermoelectric properties enable the sensing of humidity and temperature. Meanwhile, the thermoelectric receptor can differentiate mechanical stimuli from temperature by the voltage. The development enables a wide range of sensory capabilities of traditional e-skin and expands the applications in real life.

Skin-Inspired Multi-Modal Mechanoreceptors for Dynamic Haptic Exploration

Active sensing is a fundamental aspect of human and animal interactions with the environment, providing essential information about the hardness, texture, and tackiness of objects. This ability stems from the presence of diverse mechanoreceptors in the skin, capable of detecting a wide range of stimuli and from the sensorimotor control of biological mechanisms. In contrast, existing tactile sensors for robotic applications typically excel in identifying only limited types of information, lacking the versatility of biological mechanoreceptors and the requisite sensing strategies to extract tactile information proactively. Here, inspired by human haptic perception, a skin-inspired artificial 3D mechanoreceptor (SENS) capable of detecting multiple mechanical stimuli is developed to bridge sensing and action in a closed-loop sensorimotor system for dynamic haptic exploration. A tensor-based non-linear theoretical model is established to characterize the 3D deformation (e.g., tensile, compressive, and shear deformation) of SENS, providing guidance for the design and optimization of multimode sensing properties with high fidelity. Based on SENS, a closed-loop robotic system capable of recognizing objects with improved accuracy (≈96%) is further demonstrated. This dynamic haptic exploration approach shows promise for a wide range of applications such as autonomous learning, healthcare, and space and deep-sea exploration.

Ultrasensitive Touch Sensor for Simultaneous Tactile and Slip Sensing

Touch is a general term to describe mechanical stimuli. It is extremely difficult to develop touch sensors that can detect different modes of contact forces due to their low sensitivity and data decoupling. Simultaneously conducting tactile and slip sensing presents significant challenges for the design, structure, and performance of sensors. In this work, a highly sensitive sandwich-structured sensor is achieved by exploiting the porosity and compressive modulus of the sensor's functional layer materials. The sensor shows an ultra-high sensitivity of 1167 kPa-1 and a low-pressure detection limit of 1.34 Pa due to its considerably low compression modulus of 23.8 Pa. Due to this ultra-high sensitivity, coupled with spectral analysis, it allows for dual-mode detection of both tactile and slip sensations simultaneously. This novel fabrication strategy and signal analysis method provides a new direction for the development of tactile/slip sensors.

Broad-Range-Response Battery-Type All-in-one Self-Powered Stretchable Pressure-Sensitive Electronic Skin

Highly sensitive self-powered stretchable electronic skins with the capability of detecting broad-range dynamic and static pressures are urgently needed with the increasing demands for miniaturized wearable electronics, robots, artificial intelligence, etc. However, it remains a great challenge to achieve this kind of electronic skins. Here, unprecedented battery-type all-in-one self-powered stretchable electronic skins with a novel structure composed of pressure-sensitive elastic vanadium pentoxide (V2 O5 ) nanowire-based porous cathode, elastic porous polyurethane /carbon nanotube/polypyrrole anode, and polyacrylamide ionic gel electrolyte are reported. A new battery-type self-powered pressure sensing mechanism involving the output current variation caused by the resistance variation of the electrodes and electrolytes under external pressure is revealed. The battery-type self-powered electronic skins combining high sensitivity, broad response range (1.8 Pa-1.5 MPa), high fatigue resistance, and excellent stability against stretching (50% tensile strain) are achieved for the first time. This work provides a new and versatile battery-type sensing strategy for the design of next-generation all-in-one self-powered miniaturized sensors and electronic skins.

A cross-scale honeycomb architecture-based flexible piezoresistive sensor for multiscale pressure perception and fine-grained identification

Trade-off between sensitivity and the pressure sensing range remains a great challenge for flexible pressure sensors. Micro-nano surface structure-based sensors usually show high sensitivity only in a limited pressure regime, while porous structure-based sensors possess a broad pressure-response range with sensitivity being sacrificed. Here, we report a design strategy based on a cross-scale architecture consisting of a microscale tip and macroscale base, which provides continuous deformation ability over a broad pressure regime (10-4-104 kPa). The cross-scale honeycomb architecture (CHA)-based piezoresistive sensor exhibits an excellent sensitivity over a wide pressure range (0.5 Pa-0.56 kPa: S1 ∼ 27.97 kPa-1; 0.56-20.40 kPa: S2 ∼ 2.30 kPa-1; 20.40-460 kPa: S3 ∼ 0.13 kPa-1). As a result, the CHA-based sensor shows multiscale pressure perception and fine-grained identification ability from 0.5 Pa to 40 MPa. Additionally, the cross-scale architecture will be a general structure to design other types of sensors for highly sensitive pressure perception in a wide pressure range and its unit size from microscale to macroscale is beneficial for large-scale preparation, compared with micro-nano surface structures or internal pores.

Sensor-Based Wearable Systems for Monitoring Human Motion and Posture: A Review

In recent years, marked progress has been made in wearable technology for human motion and posture recognition in the areas of assisted training, medical health, VR/AR, etc. This paper systematically reviews the status quo of wearable sensing systems for human motion capture and posture recognition from three aspects, which are monitoring indicators, sensors, and system design. In particular, it summarizes the monitoring indicators closely related to human posture changes, such as trunk, joints, and limbs, and analyzes in detail the types, numbers, locations, installation methods, and advantages and disadvantages of sensors in different monitoring systems. Finally, it is concluded that future research in this area will emphasize monitoring accuracy, data security, wearing comfort, and durability. This review provides a reference for the future development of wearable sensing systems for human motion capture.